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Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) Exam Questions
- Salesforce Consultant Certifications
- Salesforce CRM Analytics and Einstein Discovery Consultant Certifications
- Topic 1: Data Layer: In this comprehensive section, Salesforce consultants delve into the heart of data extraction and loading. It's all about showcasing a deep understanding of implementing refreshes for data syncs, performing data transformations, and implementing delivery management strategies in dataflows.
- Topic 2: Security: Consultants stepping into this section will showcase their prowess in implementing necessary security settings. It covers critical aspects such as suitable dataset security settings, and the ability to implement app sharing.
- Topic 3: Admin/Configuration: This topic takes Salesforce consultants on a journey through the enablement of CRM Analytics. It tests their ability to design a solution that is suitable for data sync/dataflows/recipe limits.
- Topic 4: Analytics Dashboard Implementation: Here, consultants embark on a creative exploration of dashboard configuration, optimization of query performance using Dashboard Inspector, and using advanced functionality such as windowing.
- Topic 5: Analytics Dashboard Design: Building upon the design foundation, this section challenges candidates to bring their dashboard designs to life. It covers the technical expertise required to scope, validate, and prioritize dashboard design requirements.
- Topic 6: Einstein Discovery: This section unveils the magic of AI-driven insights and candidates' ability to analyze and choose one of the three types of predictions. It involves leveraging Einstein's advanced analytics capabilities to adjust data parameters, add or remove data and columns for the improvement of the model.
Free Salesforce Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) Exam Actual Questions
Note: Premium Questions for Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) were last updated On Mar. 25, 2026 (see below)
After the initial creation of a model, the first model insight explains
93% of the variation of the outcome variable. This is unusually high.
What is the most likely reason for this?
An CRM Analytics consultant is working with Ursa Major Solar to build a dashboard to understand customer renewals. Each subscription is captured as a Closed Won Opportunity within Salesforce and a single Account should only have one active subscription. The consultant notices the Opportunity record does NOT specify whether it is a renewal or a net new subscription.
Which data transformation should the consultant use to determine if a subscription is new or a renewal?
To determine whether a subscription is new or a renewal from the Opportunity records in Salesforce, the consultant should utilize a Custom Formula in the data transformation process. Here's the rationale:
Custom Formula Usage: By employing a custom formula, the consultant can create a logical expression that checks the historical data associated with each account. If an account has previous closed-won opportunities, any new opportunities can be labeled as renewals; otherwise, they are considered new subscriptions.
Data Insight: This method provides a straightforward way to derive new insights (new vs. renewal) directly from existing data without altering the data structure itself, making it a non-invasive and efficient solution.
Implementation: The custom formula can be applied in a recipe or directly within a dataflow in CRM Analytics, offering flexibility in how and where the transformation is executed.
Universal Containers asks a CRM Analytics consultant to review the performance of its local data sync.
After removing unused objects and fields from connected data, what else should the consultant do to improve performance of the data sync?
To improve the performance of local data sync in Universal Containers, evaluating the connection mode for each connected object is a practical approach. Here's the rationale:
Optimization of Resources: Different connection modes (e.g., Full Sync, Incremental Sync) use different amounts of resources. Choosing the right mode for each object based on how frequently its data changes can optimize the sync process and reduce load times.
Efficient Data Handling: By tailoring the connection mode to the needs of specific data objects, the overall efficiency of the data sync process is improved, leading to faster refresh rates and more timely data availability.
Cost and Performance Balance: Evaluating and selecting the appropriate connection mode can also help balance performance needs with cost constraints, as some modes may consume more compute resources than others.
The CRM Analytics consultant at Cloud Kicks is asked to a dashboard displaying Opportunities data on the account's record page. The dashboard should display only opportunity data related to the current account viewed.
How should the consultant accomplish this?
A CRM Analytics administrator is working on deploying a dashboard and a dataset from a developer sandbox to a full sandbox. They have deployed the dataset via change set and manually copy-pasted the dashboard JSON into the target org. However, they notice that the conditional formatting and the widget-specific number formats have been lost in the target environment.
What is causing this issue?
When deploying a dataset and dashboard between environments in CRM Analytics, it's essential to include the Extended Metadata (XMD) file, which controls aspects such as conditional formatting and number formatting. In this case, the administrator manually copied the dashboard JSON but did not deploy the Analytics Dataset XMD, which leads to the loss of conditional formatting and widget-specific number formats in the target environment. Including the XMD ensures that all formatting and metadata are transferred correctly.
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